Signalling for Coordinated Multi-Point Transmission and Reception (CoMP)

ABSTRACT

In a wireless communications system including a first transmission point and a second transmission point, a wireless communications method implemented in the first transmission point supporting coordinated multi-point transmission and reception (CoMP) is disclosed. The wireless communications method comprises transmitting to the second transmission point one or more CoMP hypothesis sets, and transmitting to the second transmission point a benefit metric corresponding to each CoMP hypothesis set, wherein the benefit metric can be a negative value. Other methods, systems, and apparatuses also are disclosed.

This application claims the benefit of

U.S. Provisional Application No. 61/955,559, entitled “SignalingConsiderations for Inter-eNB CoMP,” filed on Mar. 19, 2014,U.S. Provisional Application No. 61/991,055, entitled “SignalingConsiderations for NAICS,” filed on May 9, 2014,U.S. Provisional Application No. 61/991,323, entitled “SignalingConsiderations for NAICS,” filed on May 9, 2014,U.S. Provisional Application No. 62/034,724, entitled “X2 Signaling forInter-eNB CoMP,” filed on Aug. 7, 2014,U.S. Provisional Application No. 62/034,885, entitled “X2 Signaling forInter-eNB CoMP,” filed on Aug. 8, 2014,U.S. Provisional Application No. 62/055,381, entitled “Signalling forInter-eNB CoMP,” filed on Sep. 25, 2014, andU.S. Provisional Application No. 62/056,095, entitled “Signalling forInter-eNB CoMP,” filed on Sep. 26, 2014,the contents of all of which are incorporated herein by reference.

BACKGROUND OF THE INVENTION

The present invention relates to coordinated multi-point transmissionand reception (CoMP) in wireless or mobile communications and, moreparticularly, to inter-eNB (E-UTRAN NodeB or eNodeB) CoMP with NetworkAssisted Interference Cancellation and Suppression (NAICS) and/ornon-ideal backhaul (NIB).

The CoMP schemes that were discussed during the 3rd GenerationPartnership Project (3GPP) Release 11 CoMP standardization assumed theavailability of an ideal backhaul connecting the transmission points ineach cluster. This assumption allowed for coordination within thecluster based on the instantaneous channel state information (CSI)reported by the users to those transmission points. Unfortunately, suchschemes are far from being suitable when faced with a non-ideal backhaulthat has a high latency. To guide the design of schemes that areappropriate for the NIB scenario, the following agreement was reachedduring 3GPP RAN1 (Radio Access Network Working Group 1 or Radio Layer 1)Meeting #74:

For each evaluated scheme, information relating to a transmissionto/from a serving node in a given subframe should be categorized intotwo groups:

-   -   Group 1 information: information which is considered valid for a        period longer than the backhaul delay, which may therefore be        provided from a different node(s) from the serving node; and    -   Group 2 information: information which is considered valid for a        period shorter than the backhaul delay, which must therefore be        derived by the serving node.

The types of information may include for example:

-   -   CSI,    -   Allocated power per resource (including muting),    -   User equipment (UE) selection,    -   Precoding selection (including the number of transmit layers),    -   Modulation and coding scheme (MCS) selection,    -   Hybrid automatic repeat request (HARQ) process number, and    -   Transmission point (TP) selection.

Transmission layers are sometimes called “transmit layers” or “layers.”The number of transmission layers is known as “transmission rank” or“rank.” A codebook is a set of precoding matrices or precoders. Aprecoding matrix is also known as a codeword.

REFERENCE

-   [1] H. Zhang, L. Venturino, N. Prasad, P. Li, S. Rangarajan, X.    Wang, “Weighted Sum-Rate Maximization in Multi-Cell Networks via    Coordinated Scheduling and Discrete Power Control”, IEEE Journal on    Selected Areas in Communications, 29(6): pp. 1214-1224, 2011.-   [2] R1-141816, “LS on Inter-eNB CoMP for LTE,” RAN1, Mar. 31-Apr. 4,    2014.-   [3] R3-141487, “CHANGE REQUEST,” Mar. 31-Apr. 4, 2014.-   [4] R1-141206, “Signaling Considerations for Inter-eNB CoMP”, NEC,    Mar. 31 to Apr. 4, 2014.

BRIEF SUMMARY OF THE INVENTION

An objective of the present invention is to provide a suitable schemefor CoMP operation.

An aspect of the present invention includes, in a wirelesscommunications system including a first transmission point and a secondtransmission point, a wireless communications method implemented in thefirst transmission point supporting coordinated multi-point transmissionand reception (CoMP). The wireless communications method comprisestransmitting to the second transmission point one or more CoMPhypothesis sets, and transmitting to the second transmission point abenefit metric corresponding to each CoMP hypothesis set, wherein thebenefit metric can be a negative value.

Another aspect of the present invention includes, in a wirelesscommunications system including a first transmission point and a secondtransmission point, a wireless communications method implemented in thesecond transmission point supporting coordinated multi-pointtransmission and reception (CoMP). The wireless communications methodcomprises receiving from the first transmission point one or more CoMPhypothesis sets, and receiving from the first transmission point abenefit metric corresponding to each CoMP hypothesis set, wherein thebenefit metric can be a negative value.

Still another aspect of the present invention includes a firsttransmission point supporting coordinated multi-point transmission andreception (CoMP) and used in a wireless communications system. The firsttransmission point comprises a transmitter to transmit to a secondtransmission point one or more CoMP hypothesis sets and a benefit metriccorresponding to each CoMP hypothesis set, wherein the benefit metriccan be a negative value.

Still another aspect of the present invention includes a secondtransmission point supporting coordinated multi-point transmission andreception (CoMP) and used in a wireless communications system. Thesecond transmission point comprises a receiver to receive from a firsttransmission point one or more CoMP hypothesis sets and a benefit metriccorresponding to each CoMP hypothesis set, wherein the benefit metriccan be a negative value.

Still another aspect of the present invention includes a wirelesscommunications method implemented in a wireless communications systemsupporting coordinated multi-point transmission and reception (CoMP).The wireless communications method comprises transmitting from a firsttransmission point to a second transmission point one or more CoMPhypothesis sets, and transmitting from the first transmission point tothe second transmission point a benefit metric corresponding to eachCoMP hypothesis set, wherein the benefit metric can be a negative value.

Still another aspect of the present invention includes a wirelesscommunications system supporting coordinated multi-point transmissionand reception (CoMP). The wireless communications system comprises afirst transmission point, and a second transmission point to receiveform the first transmission point one or more CoMP hypothesis sets,wherein the first transmission point transmits to the secondtransmission point a benefit metric corresponding to each CoMPhypothesis set, and wherein the benefit metric can be a negative value.

Still another aspect of the present invention includes a wirelesscommunications method implemented in a transmission point (TP) used in awireless communications system. The wireless communications methodcomprises receiving, from another TP, channel state information (CSI)for a user equipment (UE), and receiving, from said another TP, useridentification for the user equipment, wherein the signaling of the CSIfor the user equipment enables user identification for the userequipment.

Still another aspect of the present invention includes a wirelesscommunications method implemented in a transmission point (TP) used in awireless communications system. The wireless communications methodcomprises transmitting, to another TP, channel state information (CSI)for a user equipment (UE), and transmitting, to said another TP, useridentification for the user equipment, wherein the signaling of the CSIfor the user equipment enables user identification for the userequipment.

Still another aspect of the present invention includes a transmissionpoint (TP) used in a wireless communications system. The TP comprises areceiver to receive, from another TP, channel state information (CSI)for a user equipment (UE) and user identification for the userequipment, wherein the signaling of the CSI for the user equipmentenables user identification for the user equipment.

Still another aspect of the present invention includes a transmissionpoint (TP) used in a wireless communications system. The TP comprises atransmitter to transmit, to another TP, channel state information (CSI)for a user equipment (UE) and user identification for the userequipment, wherein the signaling of the CSI for the user equipmentenables user identification for the user equipment.

Still another aspect of the present invention includes a wirelesscommunications method implemented in a wireless communications system.The wireless communications method comprises transmitting, from atransmission point (TP) to another TP, channel state information (CSI)for a user equipment (UE), and transmitting, from the transmission point(TP) to said another TP, user identification for the user equipment,wherein the signaling of the CSI for the user equipment enables useridentification for the user equipment.

Still another aspect of the present invention includes a wirelesscommunications system comprising a first transmission point (TP), and asecond transmission point (TP) to transmit to the first TP, channelstate information (CSI) for a user equipment (UE) and useridentification for the user equipment, wherein the signaling of the CSIfor the user equipment enables user identification for the userequipment.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a block diagram of a CoMP system.

FIG. 2 depicts a CoMP coordination request under CoMP-NIBimplementation.

FIG. 3(a) depicts an example of centralized CoMP coordination via CoMPhypothesis and Benefit metric over X2.

FIG. 3(b) depicts an example of centralized CoMP coordination via CoMPhypothesis and Benefit metric over X2. Note here that the BM is used toconvey the utility change for a particular resource allocation indicatedin the associated CH to the Master node. The CH sent by the Master nodecontains the resource allocation decision.

FIG. 4 depicts an example of distributed CoMP coordination via CoMPhypothesis and Benefit metric over X2.

FIG. 5 depicts that if only “gains” can be conveyed via benefit metric,eNB2 may not obtain the information about the loss it can cause to eNB1by increasing its power. Consequently, such an increase in power wouldhave to be done unilaterally by eNB2 which is undesirable.

DETAILED DESCRIPTION

Referring now to FIG. 1, a CoMP mobile communications system 400comprising a CoMP coordination zone or area or CoMP cooperating set 402in which the embodiments may be implemented is illustrated. One or moreuser equipments 410 are served by one or more TPs or cells 404 to 408.TPs 404 to 408 can be base stations or eNBs. Each of the user equipmentsincludes e.g. a transmitter and a receiver, and each of the basestations or eNBs 104 includes e.g. a transmitter and a receiver.

Embodiment A

We have captured the details of the scheduling framework in theappendix. We assume that for each user a measurement set containingup-to three TPs among those in the coordination zone is defined and heldfixed for a time scale even coarser than the one at which thecentralized decisions (precoder tuple or muting pattern assignment andpossibly user association) are made.

From the description given in the appendix, we see that to determine thecentralized decisions (such as the precoder tuple assignment and theuser associations) under the full buffer traffic model, the designatedcentral node (referred to here as the master TP (MTP)) should be able toobtain, R_(u) ^(b)(Ŵ), which we recall denotes an estimate of theaverage rate that user u can obtain (over the available time-frequencyresource normalized to have size unity) when it is served data by TP b,given that the precoder tuple Ŵ is assigned to the TPs in the zone andthat no other user is associated with TP b. Recall also that theprecoder tuple Ŵ can also correspond to a muting pattern deciding whichTPs should be active and which should be turned off in thetime-frequency unit. For the joint semi-static point muting (SSPM) andsemi-static point switching (SSPS) scheme (cf. (P1) in the appendix),this average estimate R_(u) ^(b)(Ŵ) must be obtained for each user u,each TP b in its measurement set and for all precoder tuple assignments.Note that for any precoder tuple, R_(u) ^(b)(Ŵ) can be considered to benegligible if the TP b is not in the measurement set of user u. Noticealso that R_(u) ^(b)(Ŵ) can be assumed to be equal to R_(u) ^(b)(Ŵ′) forany two precoder tuple assignments Ŵ and Ŵ′ which differ only inprecoders assigned to TPs not in the measurement set of user u. For theSSPM problem (cf. (P2) in the appendix) with pre-determined userassociations, the average estimate R_(u) ^(b)(Ŵ) must be obtained foreach user u only for its pre-determined serving TP b, but the set ofusers associated to that TP must also be obtained. Thus, the followingtypes of backhaul signaling are needed to facilitate a centralizedimplementation.

A1. Backhaul Signaling to Enable Determination of Centralized Actions(Such as Precoder Tuple/Muting Pattern Assignments and the UserAssociations)

We will now consider computation of the average rate estimates {R_(u)^(b)(Ŵ)} at the MTP for some user u, under a precoder tuple assignmentŴ. These rates depend on the channels that the user sees from TPs in itsmeasurement set. Using up-to three CSI processes (recall that themaximum measurement set size is three) which include a commoninterference measurement resource (IMR), the UE can report short-termCSI for each TP b in its measurement set, where this short-term CSI iscomputed based on the non-zero CSI-reference signal (RS) transmitted byTP b and the interference observed on the IMR, which in turn includesonly the interference from TPs not in the measurement set of user u. TheUE currently reports such CSI only to its designated anchor TP.

However, to fully exploit point switching gains we need to allow for thepossibility of associating a user to a non-anchor TP and then allowingthat user to report instantaneous (short-term) CSI to the non-anchor TPit has been associated to. Further, the CSI processes should be definedin a coordinated manner so that the users measure the appropriateinterference on the constituent IMRs. Such coordinated configuration ofIMRs also provides the ability to inject the desired interference (suchas isotropically distributed interference) onto resource elements inthose IMRs.

These short-term CSI can be sent to the MTP over the backhaul, which canthen filter (i.e. perform a weighted average of) the received CSIsequence to obtain an averaged channel estimate H_(u) ^(b) for each TP bin the measurement set of user u. Alternatively, the averaging (orsubsampling) of the short-term CSI can be done by the TP receiving theshort-term CSI but where the averaging window (and possibly theweighting factors or subsampling factors) can be configured for that UEon a per CSI-process basis.

In either case, these averaged or subsampled channel estimates for allTPs in that UE's measurement set can be used by the MTP to compute R_(u)^(b)(Ŵ) for each precoder tuple hypothesis Ŵ and if needed each TP b inits measurement set, under the assumption that the signal transmitted byeach TP (along its assigned precoder under that hypothesis) isisotropically distributed. Another option is for the MTP to directlycompute an estimate of the rate using each received short-term CSI andthen average these computed rates to obtain an estimate of the averagerate. We note that in case each precoder tuple hypothesis is a mutingpattern, the average rate estimates can be computed using only theaverage received powers observed by each user from each TP in itsmeasurement set. In such a case only reference signal received powers(RSRPs) need to be exchanged for a configurable set of users over thebackhaul.

Moreover, the signaling of CSI (which can be RSRP) over the backhaulshould enable the identification of the users whose CSI are beingsignaled as well as the attributes (such as zero-power CSI-RS ornon-zero-power CSI-RS) of the corresponding CSI processes. Recall alsothat in the scenario with pre-determined users associations, the set ofusers associated to each TP in the zone needs to be exchanged orconveyed to the MTP.

These views are summarized in the following proposal.

Proposal: Signaling of averaged or subsampled CSI obtained over CSIprocesses corresponding to a configurable set of users should beconsidered. Coordination in configuring these CSI processes should beallowed.

Proposal: Possibility of configuring a user to report short-term CSI tomore than one TP or a chosen TP in a configurable set of TPs should beconsidered.

Next, in the more general finite buffer model estimates of the queuesizes are needed to determine each coarse (centralized) action, whereeach such user queue size represents the amount of traffic that wouldavailable for transmission to serve that user until the next coarseaction. Determining estimates of these queue sizes requires the TPs toreport their most-recently updated associated user queue sizes beforethe next coarse action to the MTP.

Proposal: Signaling of associated user queue sizes by a TP to another TPshould be considered, possibly by enhancing the status report.

A2. Backhaul Signaling from MTP to TPs

Each TP in the coordination zone is informed (semi-statically) about theprecoder it should use and possibly the users it should serve on atime-frequency resource. The decision made by the MTP can be representedusing a CoMP hypothesis. This can be achieved for instance, by assigningan identifier to each TP in the coordination zone and then includingpairs representing (TP identifier, corresponding part of decision) inthe CoMP hypothesis. Each TP then implements its own per-subframescheduling based on the instantaneous CSI it receives from the usersassociated to it. Some comments on the set Ψ which contains the set ofprecoders that can be assigned to each TP, are on order. We recall thatthis set includes codeword 0 to subsume muting as a special case. It canalso include codewords of the form αI where α denotes a positive powerlevel. In addition, it can include sector beams as its codewords. Noticethat so far we have implicitly assumed that each TP will accept thedecision made by the MTP. This assumption need not always hold, in whichcase it is beneficial (even necessary) to have an acknowledgement fromthe receiving TP conveying whether or not it accepts to implement itspart of the decision in the CoMP hypothesis.

Note that since the decision represented by the CoMP Hypothesis shouldbe valid for a period longer than the (maximum) backhaul delay.Henceforth we will refer to the time period over which a CoMP hypothesisis supposed to be valid (or supposed to apply) as a frame. Thus, theCoMP hypothesis should be signaled at a time granularity (i.e., the timeinterval between successive CoMP hypotheses) that is a multiple of thelargest backhaul delay. Note that it in some scenarios it may bepreferable for the MTP to receive the acknowledgement, in which case themultiple should be at-least 2. A small value of this multiple would helpthe system adapt faster, so we suggest a value for this multiple that isless than or equal to 3.

Proposal: Signaling of decisions made by one TP (such as precoder set ormuting pattern assignment) to all other TPs over the backhaul should beconsidered. Such a decision can be represented by a CoMP Hypothesis.Signaling of an acknowledgement conveying a yes/no response to areceived CoMP hypothesis should be considered.

A3. Distributed Implementation

In order to enable a de-centralized or distributed operation, a benefitmetric corresponding to each CoMP hypothesis can be defined. In [1] adistributed implementation of power control is provided. An exampledistributed operation considering binary power control is described nextand we note that extension to multiple power levels can be developedfollowing the same approach. Each TP b in the coordination set candetermine its set of interfering TPs, where a TP is labelled interferingfor TP b if it is in the measurement set of at-least one user associatedto TP b. Note that TP b can determine its set of interfering TPs.Further, let us refer to all TPs in whose interfering sets TP b ispresent as the out neighbor set of TP b. Each CoMP hypothesis can bedefined such that the sending TP, say TP b, suggests a muting (or ingeneral a power level) pattern for a set of time-frequency resources toa receiving TP, say TP a, in its interfering set of TPs. The benefitmetric for that hypothesis comprises of a set gain (or loss, i.e., thegain can be negative) values (one for each time-frequency resource),where each gain represents the incremental average throughput or utilitythat would be achieved for the sending node (TP b) if the receiving node(TP a) accepts the suggested muting or power level (henceforth termedsuggested action) on that time-frequency resource, while the other TPsin the interfering set of TP b as well as TP b do not alter theircurrent status (current power level). TP a can then consider eachtime-frequency resource and add up all the gain values it has receivedfor each suggested action on that resource. To this sum it can then addthe gain (or loss) that it would obtain upon following the suggestedaction, assuming that all TPs in its interfering set do not alter theircurrent status. This sum gain for each action can then represent thesystem utility gain that can be achieved by a one-step change, i.e., theincremental throughput or utility gain for the coordination set achievedwhen TP a accepts that suggested action on that resource and all theother TPs in the coordination set keep their current respective status.TP a can then independently choose its action on each time-frequencyresource using a probabilistic rule [1], and this distributed operationcan be shown to converge. Further, the TP a can signal its choice ofactions using an enhanced RNTP. Note here that as an alternative theCoMP hypothesis can consider only one time-frequency resource andsuggest multiple actions, one for each TP in its interfering set and thecorresponding benefit metric can include a gain (or a loss) for eachsuggested action. In general, the CoMP hypothesis can include multipletuples, where each tuple contains a TP identifier and a suggested actionidentifier, and one time-frequency resource identifier that is commonfor all tuples in that hypothesis. Alternatively, each tuple can includea time-frequency resource identifier and a suggested action identifierwhile the hypothesis includes a TP identifier that is common across allits constituent tuples. Combinations of these two general alternativescan also be used to define a CoMP hypothesis. In each case the benefitmetric includes a gain (or loss) for each suggested action and a TPreceiving the benefit metric must be able to determine which gaincorresponds to which suggested action.

We next discuss efficient signaling mechanisms. First note that in orderto reduce the signaling overhead, the network can configure to allowonly a subset of TPs in the coordination set to make a change. This canbe done in a de-centralized manner using a pre-determined function(known to all TPs in the coordination set), where this function returnsthe indices (or identifiers) of all TPs that are permitted to make achange, given the frame or sub-frame index as input. Alternatively, adesignated TP can convey the set of TPs that are permitted to make achange, to all the other TPs in the coordination set, at the start ofeach frame. In either case, a TP b will send one or more CoMP hypothesisfor TP a and corresponding benefit metrics, only if TP a is in itsinterfering set and TP a is in the set of TPs that are permitted to makea change on that frame. Further, the cardinality of the aforementionedset of TPs can be used to control the backhaul signaling overhead, aswell as the size of the enhanced relative narrowband TX power (RNTP)which is used by each TP in that set to convey its actions to the otherTPs. Note that each TP which changes its action on a time-frequencyresource must report its changed action only to TPs in its out neighborset.

Note that the distributed procedure described above can be implementedindependently on each time-frequency resource. Then, the set of timefrequency resources on which TPs can change their actions in a frame canalso be controlled to reduce the signaling overhead. This can beaccomplished as before, for instance by defining a rule using the frameindex (known to all TPs in the coordination set) to decide the set oftime-frequency resources at the start of each frame. A combination isalso possible where in each frame a set of TPs which are permitted tochange their actions and a set of time-frequency resources on whichthose TPs can change their actions is identified for each frame.

The configuration (or identification) of these sets can instead be doneat a time-scale coarser than the frame duration, i.e. once in every nframes, where n is configurable. We have assumed that the set of TPspermitted to change their actions is the same across all time-frequencyresources in the set of such resources. A more general approach would beto configure a separate set of TPs for each time-frequency resource.Here a designated node can optionally be used convey the configured setsto all other TPs.

However, a potential drawback with the distributed approach describedabove is if the benefit metrics do not allow a TP to infer (a goodapproximation of) the system utility gain (or loss) accrued by asuggested action on a time-frequency resource, in which case oscillatorybehavior or convergence to a highly sub-optimal operating point canresult. We summarize our views in the following proposal.

Proposal: The benefit metrics received by a TP should enable it tocompute a system utility change for each action suggested for that TP ineach of its received CoMP hypothesis.

Thus, we provided our views on backhaul signaling needed for CoMP-NIBcomprising of the following proposals:

Proposal: Signaling of averaged or subsampled CSI obtained over CSIprocesses corresponding to a configurable set of users should beconsidered. Coordination in configuring these CSI processes should beallowed.

Proposal: Possibility of configuring a user to report short-term CSI tomore than one TP or a chosen TP in a configurable set of TPs should beconsidered.

Proposal: Signaling of associated user queue sizes by a TP to another TPshould be considered, possibly by enhancing the status report.

Proposal: Signaling of decisions made by one TP (such as precoder set ormuting pattern assignment) to all other TPs over the backhaul should beconsidered. Such a decision can be represented by a CoMP Hypothesis.Signaling of an acknowledgement conveying a yes/no response to areceived CoMP hypothesis should be considered.

Proposal: The benefit metrics received by a TP should enable it tocompute a system utility change for each action suggested for that TP ineach of its received CoMP hypothesis.

Embodiment B

We present our views on the signalling that is appropriate to extractnetwork assisted interference cancellation and suppression (NAICS) gain.

We assume that a candidate list of potentially interfering cells isconfigured by the network for the user of interest. For each cell inthis list (identified by an index, a natural choice of which is thecorresponding cell ID) the network can specify a set of parameters. Sucha candidate list (along with its constituent parameters) should besemi-statically configured by the network for the user in order tosimplify and assist the user's blind detection.

B1. Signaling Parameters Pertaining to Reference Signal (RS)

B1.1 Signaling Parameters Associated with the Cell-Specific ReferenceSignal (CRS)

We first consider the signalling needed to convey parameters associatedwith the CRS transmitted by each cell in the candidate list. In ourview, the number of CRS ports for each cell in the list (and optionallyits corresponding frequency shift or the multimedia broadcast multicastservice (MBMS) or single frequency network (MBSFN) sub-frameconfiguration) is quite beneficial in reducing the blind detectioncomplexity at the user of interest. In this context, we note that thepossibility of CRS not being transmitted at-all by the interferer mightalso need to be considered by the user over any sub-frame in order toincorporate dynamic cell ON-OFF. Another useful parameter is the(expected) physical downlink shared channel (PDSCH) start symbol. Thesignalling of this parameter conveys the actual (or likely) startingsymbol of the interfering PDSCH and is needed to fully exploit NAICSgain (over all transmitted interfering PDSCH symbols). Moreover, blinddetection of the starting symbol by the user appears to be quitechallenging.

B1.2 Signaling CSI-RS Related Parameters

Next, we consider configuration parameters associated with the CSI-RS(including both zero-power and non-zero power CSI-RS). In this case, theuser upon knowing one or more CSI-RS configurations that can be employedby each potential interferer in its list, knows the PDSCH resourceelement (RE) mappings possible under each such interferer hypothesis,which clearly will improve interference cancellation/suppression gains(for a given feasible level of complexity).

On the other hand, signalling for quasi co-location (QCL) indicationneeds further evaluation since purely demodulation reference signal(DMRS) based channel estimation was sufficient for desired signaldemodulation in several evaluated instances during 3GPP Release 11 andit is unclear if enhanced estimation of the channel seen from aninterferer is really needed for cancellation/suppression gains.

In summary, we have the following proposal for the parameters pertainingto the RS.

Proposal: Convey via semi-static signaling about each cell in acandidate list:

-   -   (1) Number of CRS ports and PDSCH start symbol    -   (2) CSI-RS configuration(s)

B2. Signalling to Aid Blind Detection of Other Dynamic Parameters

B2.1 Modulation Classification

We note that the joint blind detection of modulation, PMI, RI andpresence of one dominant interferer using a CRS based TM (transmissionmode) has been deemed feasible for 2 CRS ports, at-least under thesimulated scenarios and provided that the other required parameters areperfectly known. Similarly, in the case of DMRS based TM, joint blinddetection of modulation, nSCID and presence of one dominant interfererusing up-to two DMRS ports (ports 7 and 8) has been deemed feasible,again under the simulated scenarios and provided that the other requiredparameters are perfectly known.

However, the evaluation so far has assumed only the three modulationtypes that can be employed up-to 3GPP Release 11, i.e., quadrature phaseshift keying (QPSK), 16 quadrature amplitude modulation (QAM) and 64QAM. It is likely (or imminent) that a higher modulation order (256 QAM)will be agreed in 3GPP Release 12. This then raises the question aboutfeasibility of blind detection in scenarios where 256 QAM can beemployed by the interferer. In this context, we note that applying blindmodulation classification when multiple higher order modulation typescan be employed by the interferer is more complicated (indeed theclassification errors tend to be increasing with the modulation order).Moreover, NAICS gain (even after correctly classifying an interfereremploying a higher order modulation) over the baseline interferencerejection combining (IRC) receiver will be smaller, since the IRCreceiver regards interference as a (un-constrained) Gaussian variable,an assumption that becomes increasingly suitable for denser QAMconstellations. To summarize, support of 256 QAM with NAICS needs to befurther evaluated. Our preference is thus the following.

Proposal: Blind modulation classification is done by the user assumingthat QPSK, 16 QAM and 64 QAM are the modulation types that can beemployed by any interferer.

It is desirable that the assumption made by the user is indeed respectedby each interferer in its candidate list, i.e., it is desirable that thenetwork enable NAICS functionality only in the regime where 256 QAM isnot employed in a cluster of cells. In case, this is not true, the usercan itself disable its NAICS capability and fallback to IRC basedreception, following some decision rule, when it perceives degradedperformance due to operation in a scenario where 256 QAM is oftenemployed by one or more interferers.

B2.2 Supporting 4TX

The support for 4TX is important and NAICS gain should hold for suchdeployments. Let us consider the case where the dominant 4TX interfereremploys a CRS-based TM. Here, blind detection of the assigned transmitrank of the interferer among all the four possible transmit ranks canresult in an excessive complexity expended to chase gains that becomeincreasingly marginal for larger ranks. It is thus meaningful torestrict the transmit rank assigned by the interferer. The user can beinformed via semi-static signaling about an upper bound to the transmitrank that can be assigned by each potentially interfering cell in itscandidate list. Alternatively, the semi-static signaling can indicate anexpected transmit rank that is likely to assigned by that interferer,which can be used as a more probable seed value for the blind detectionimplementations.

Next, we suppose a dominant interferer (from the candidate list)employing a DMRS based TM. In this case, physical resource block(PRB)-pair has been agreed as the minimum resolution of thetime-frequency unit that can be assigned by any such interferer.

Here, it is particularly beneficial if the user has to consider onlyports 7 and 8 in order to detect the presence and absence of interfererand classify the rank on each PRB-pair, possibly by determining thenorms of the columns of the corresponding equivalent channel estimate.Recall that joint blind detection has been deemed feasible only withsuch a qualification. Consequently, semi-static signaling a transmitrank upper bound adhered to by each potential interferer is useful hereas well.

Proposal: Convey via semi-static signaling about each cell in acandidate list:

-   -   An upper bound on the transmit rank that can be assigned.

B3. Other Issues

We believe that synchronization should be assumed by the user withoutany explicit signaling since this is in any case the main operatingregime where NAICS gain can be achieved in a feasible manner. While, theuser can itself disable its NAICS capability and fallback to IRC basedreception, following some decision rule, when it perceives degradedperformance due to operation in an asynchronous scenario, it isdesirable that the network enable NAICS functionality only in thesynchronous regime.

The user can perform blind detection (classification) after assuming acertain minimum time-frequency unit that can be assigned by aninterferer under each transmission scheme, in other words, afterassuming that the parameters that it seeks to classify remain constantwithin that unit. This minimum assignable time-frequency unit can be setor assumed, for instance, to be one PRB-pair. This is a choice that isindeed accurate at-least for DMRS based TMs and has been found to ensurereliable blind detection. One PRB-pair for all DMRS based TMs has beenfound sufficient to ensure reliable blind detection. For CRS based TMsthe minimum assumed unit can be configured (by the network for the user)to be either a slot or a PRB pair. It is beneficial with respect toNAICS gain that this assumption is indeed respected by each interfererin the list, i.e., it is desirable that the network enable NAICSfunctionality only in the regime where the respective assumed minimumassignable time-frequency units are followed by all the cells. Then,note that configuring the minimum assumed unit for CRS based TMs to be aslot makes blind detection challenging but does not preclude distributedvirtual resource block (DVRB) based allocation, while configuring theminimum assumed unit to be a PRB-pair makes blind detection morefeasible but precludes DVRB based allocation. While these assumedminimum assignable time-frequency units can be made further configurableon a per-interferer basis for each user, i.e., the assumed minimumassignable time-frequency units can be altered semi-statically for eachcell in that user's candidate list of interferers, further evaluation isneeded to assess if this is beneficial. This is because such semi-staticconfiguration in the absence of any explicit scheduling restrictionswill not lead to significant NAICS gain, while placing schedulingrestrictions can be counter-productive due to the bursty nature of thetraffic. In this context, we note that a significant portion of thetraffic is expected to be bursty and formed by very small per-user datademands.

Proposal: Interference cancellation/suppression is attempted by the userassuming synchronization and a minimum time-frequency unit that can beassigned by a dominant interferer for each transmission scheme.

We note that in case the assumed minimum assigned unit is configured tobe a slot for the CRS based TMs, it is still possible to exploit forblind detection the fact that the minimum unit can be more than a slot(i.e., can be a PRB-pair) even under CRS based TMs when the resourceallocation is not DVRB based.

Finally, for each cell in the candidate list of the user, a possible setof transmission schemes that could be utilized by that cell, should bespecified. This will obviously reduce the blind detection complexity atthe user end and will also enable the network to configure the bestpossible scenario for NAICS (if deemed beneficial by the network), wherethe users sees the same transmission scheme (such as a DMRS basedscheme) being used by both the serving cell and the interferer.

B4. Benefit Metric in Coordinated Multi-Point Transmission and Receptionwith Non-Ideal Backhaul (CoMP-NIB)

With reference to FIG. 2, in order to allow CoMP-NIB implementation,CoMP coordination request including (but not limited to) the followingscan be sent from one eNB to another:

-   -   One or more CoMP hypotheses, each comprising a hypothetical        resource allocation associated with a cell ID, where the cell        identified by the cell ID is not necessarily controlled by the        receiving eNB,    -   A benefit metric associated with one or more CoMP hypothesis/es,        quantifying the benefit that a cell of the sender node expects        in its scheduling when the associated CoMP hypothesis/es is        assumed, and    -   Necessary time/frequency granularity and signaling period: Same        as the associated CoMP hypothesis/es.

Consider the benefit metric associated with one CoMP hypothesis andsuppose that the cell ID in that hypothesis identifies a cell controlledby the receiving eNB. The intention of benefit metric is to help thereceiving eNB gauge the benefit that will be accrued by the sending eNB,if it follows the suggestion in the associated CoMP hypothesis. Thereceiving eNB can weigh this benefit against the loss it might accrueupon following that suggestion, and then decide its response. However,implicit in the derivation of this cell-specific benefit metric is theuse of a reference state that the sending eNB assumes for the receivingeNB (or equivalently for the cell identified by the ID) over thetime-frequency resource indicated in the CoMP hypothesis. For instance,if the CoMP hypothesis suggests “muting” (or zero power-level) over atime-frequency resource, the sending eNB could have computed the benefitmetric after assuming a reference state of non-muting (i.e., a certainnon-zero power level) for the receiving eNB over the same indicatedtime-frequency resource. In the multi-vendor scenario and particularlyin the case when multiple power levels (not just binary) can beindicated via a CoMP hypothesis, it is desirable that the referencestate used to by each sending eNB in deriving its benefit metric beknown to the receiving eNB, so that the latter can properly decide itsresponse. This can be done without explicit signaling if it is agreedthat the benefit metric is computed by each sending eNB using apre-defined reference state. This pre-defined reference state can forinstance be the highest power level that can be used over atime-frequency resource or it can be the current power level being usedby the receiving eNB over the time-frequency resource.

Next, let us consider a common benefit metric associated with multipleCoMP hypotheses.

Here, again the aforementioned reference state can be assumed for allcells indicated via their IDs in the multiple hypotheses. The use ofbenefit metric is better justified when it is associated to onehypothesis rather than multiple hypotheses, since in the latter case itis not possible to determine which individual hypothesis contributeswhat fraction of that overall common benefit metric. Consequently, for agiven number of bits available to convey the benefit metric, the rangeof the benefit metric must be optimized for the case when it is used foran individual hypothesis rather than multiple hypotheses. Further, as analternative, a scaling factor for the benefit metric should beseparately configurable (on a per-eNB basis if needed). Then, thereceiving eNB can scale the received benefit metric by the scalingfactor associated with the sending eNB (which could be common for alleNBs or as an option could be configured separately for each sendingeNB) to decide its response. Another alternative would be for each eNBto obtain a time average of the benefit metrics sent by a sending eNBand then determine the scaling factor for that sending eNB using thataverage.

Embodiment C

In 3GPP RAN3 Meeting #84, the following agreements on X2 messages tosupport the inter-eNB CoMP were reached [3]:

“The task of inter-eNB CoMP is to coordinate multiple eNBs in order thatthe coverage of high data rates and the cell-edge throughput areimproved, and also the system throughput is increased. The coordinationof multiple eNBs is achieved by signalling between eNBs of hypotheticalresource allocation information, CoMP hypotheses, associated withbenefit metrics. Each of the signalled CoMP hypotheses is concerned witha cell belonging to either the receiving eNB, the sending eNB or theirneighbour. The benefit metric associated with the CoMP hypothesesquantifies the benefit assuming that the CoMP hypotheses are applied.The receiving eNB of the CoMP hypotheses and the benefit metrics maytake them into account for RRM and may trigger further signalling FFS.RSRP measurement reports can also be exploited for inter-eNB CoMP. Forexample, the RSRP measurement reports can be used to determine and/orvalidate CoMP hypotheses and benefit metrics. [Further explanation onthe RSRP measurement reports of UEs: FFS] Inter-eNB CoMP is located inthe eNB.”

In the following, we provide our views along with the required messagestructure.

C1.1 CoMP Hypothesis for Inter-eNB CoMP

Each CoMP hypothesis (CH) contains a hypothetical resource allocationfor a cell that is not necessarily controlled by the receiving eNB. Thedesign of signaling associated with such CoMP hypotheses must facilitateboth centralized and distributed radio resource management (RRM). Incentralized RRM a potential use of CH would be a mandatory resourceallocation that the cell indicated in that CH will (or must) follow,whereas in a distributed RRM scenario the CH would be a request whichthe indicated cell may or may not follow. As a result, including anelement in the CH to indicate whether the constituent resourceallocation is mandatory or not, is desirable. This element is alsouseful when the CH is sent to the eNB not controlling the indicatedcell, since then the latter eNB can have more information about thepossible resource allocation of neighboring cells, to make its ownresource allocation decision. We note that when the CH is used to conveya mandatory resource allocation (or a final decision of centralized RRM)there is limited use of the associated benefit metric. Thus, oneapproach of realizing the element would be via a special value of thebenefit metric. In particular, when the associated benefit metric isnull or set to that special value then the resource allocation in the CHis mandatory, otherwise, the resource allocation is not mandatory. Anexample of centralized coordination is given in FIGS. 3(a) and 3(b), andthat of a distributed coordination is given in FIG. 4. Note that in thedistributed case, eRNTP can be used to convey the resource allocationdecisions.

Proposal C1: Include an element in CoMP hypothesis message to indicatewhether the included resource allocation for the indicated cell ismandatory or not.

Another relevant point here is that a cell needs to be indicated in theCH using an ID. This ID should be unique for each cell. This requirementrules out using the physical cell ID, since in certain deploymentsmultiple neighboring cells (or transmission points) can share the samephysical cell ID. It is nevertheless important to be able to specify orsignal a CH for a particular cell among a set of cells sharing the samephysical cell ID.

C1.2 Benefit Metric

We first consider the role of benefit metric in a distributed setup. Insuch a case the cell indicated in the associated CoMP hypothesis willtypically be controlled by the receiving eNB. Then, the intention ofbenefit metric (as stated in RAN1 proposals such as [4]) is to help thereceiving eNB gauge the benefit that will be accrued by the sending eNB,if it follows the suggested resource allocation in the associated CoMPhypothesis. The receiving eNB can then add up all the metrics itreceives for a particular cell controlled by it and a particularresource allocation, and compare the sum against the gain or loss itmight incur, in order to decide the resource allocation for its cell.For the receiving eNB to make a decision that will lead toward a socialoptima, it should have information about the loss it can cause to othereNBs by certain allocation (such as power boosting on some PRB that wasmuted previously in response to a request). This point is illustrated inFIG. 5. Moreover, in the case the cell identified by the sending eNB iscontrolled by the sender, a negative value can be used to convey theloss the sending eNB can incur by muting a certain resource. Forinstance, we note that the sign of the benefit metric value can beseparately conveyed via a separate binary valued element in the benefitmetric field, which is one if the metric is positive and is zerootherwise, or vice versa.

Proposal C2: Allow negative values in the benefit metric.

The guiding principle behind benefit metric was that it could be used toconvey the change in a utility function in a succinct manner. Theutility function usually depends on several factors such as queue sizes,channel states, priorities (or quality of service (QoS) classes) of theusers being served by that eNB or cell. The benefit metric has thepotential to convey the change resulting from a hypothetical resourceallocation, without the need of signaling all the constituent terms ofthe utility function. However, this potential can be realized only ifthe benefit metric field is large enough. Moreover, a potentiallyserious drawback of not having a benefit metric field that allows for afine quantization of the utility change is that it can lead tooscillatory behavior in distributed coordination. An additional use of alarger benefit metric field is that it provides the operator theflexibility to simultaneously convey different utility changes for thesame hypothetical resource allocation (or set of resource allocations inthe CoMP hypothesis set associated with that benefit metric), where eachsuch change can be computed by emphasizing different terms of theutility function.

Proposal C3: The benefit metric field should be sufficiently large,e.g., 3 bytes or 2 bytes.

It has been agreed that a single benefit metric can be associated withmultiple CoMP hypotheses, i.e., a CoMP hypothesis set. Consider such ascenario where one benefit metric is associated with L hypotheses in aCoMP hypothesis set. In such a case, where L>1, it will be helpful ifthe benefit metric field represents a string of L+1 numbers. This willenable differential encoding of benefit metric. For instance, the firstnumber could be the base value (quantized by a certain number of bits,where that number is less than the benefit metric field size which isfor instance 3 bytes or 24 bits) which represents the utility changewhen all the resource allocations are together applied. On the otherhand, each of the other L numbers can be offsets (represented by Δ bitseach) computed with respect to the base value, such that the sum of thebase value and the offset captures the utility change when only thecorresponding individual resource allocation is applied. It is wellestablished that differential encoding allows for finer quantization fora given payload size. Note that L and Δ can be separately conveyed andare configurable, for instance L can be conveyed in the range of theCoMP hypothesis set. So L=1 or Δ=0 would mean that the benefit metricreduces to a single number that is common for all the associatedhypothesis or hypotheses. An alternative benefit of this differentialencoding feature is that it provides the operator the flexibility toconvey different utility changes for the same hypothetical resourceallocation, where each such change can be computed by emphasizingdifferent terms of the utility function. Note that the value of L canvary between 1 and a maximum, denoted by maxnoofCoMPCells. Examplevalues for maxnoofCoMPCells are 4, 8, 16, or 256. We note here that alarger value of maxnoofCoMPCells can help to reduce overhead (since asingle benefit metric field is associated with all the hypotheses in theset) and is useful if the CoMP hypothesis set is being used to conveythe final decision in a centralized RRM, since in that case theassociated single benefit metric value can be set to a special value (ornull) to indicate that the hypothesis set is mandatory.

Proposal C4: Differential encoding of the benefit metric field should besupported.

We discussed the necessary X2 message to support the inter-eNB CoMP.

C2. Text Proposal

9.2.xx CoMP Information

This Information element (IE) provides the list of CoMP hypothesis sets,where each CoMP hypothesis set is the collection of CoMP hypothesis(es)of one or multiple cells and each CoMP hypothesis set is associated witha benefit metric.

Example-1a

IE type and Semantics IE/Group Name Presence Range reference descriptionCoMP Information 1 . . . Item <maxnoofCoMPInformation> >CoMP HypothesisM 9.2.xy Set >Benefit Metric M BIT STRING The first left most bit: (SIZE(24)) value “1” means positive benefit and value “0” means negativebenefit. The remaining bits quantize the magnitude of benefit. All bitswith value “0” represent the special value that denotes CoMP HypothesisSet IE is mandated indication by the sending eNB. [>Time Granularity:FFS] [Starting SFN: FFS] [Starting Subframe Index: FFS] Range boundExplanation maxnoofCoMPInformation Maximum number of CoMP Hypothesissets. The value is FFS.

Example-1b

IE type and Semantics IE/Group Name Presence Range reference descriptionCoMP Information 1 . . . Item <maxnoofCoMPInformation> >CoMP HypothesisM 9.2.xy Set >Benefit Metric M BIT STRING The first left most bit: (SIZE(24)) value “0” means positive benefit and value “1” means negativebenefit. The remaining bits quantize the magnitude of benefit. All bitswith value “0” represent the special value that denotes CoMP HypothesisSet IE is mandated indication by the sending eNB. [>Time Granularity:FFS] [Starting SFN: FFS] [Starting Subframe Index: FFS] Range boundExplanation maxnoofCoMPInformation Maximum number of CoMP Hypothesissets. The value is FFS.

Example-2a

IE type and Semantics IE/Group Name Presence Range reference descriptionCoMP Information 1 . . . Item <maxnoofCoMPInformation> >CoMP HypothesisM 9.2.xy Set >Benefit Metric M BIT STRING The first left most bit: (SIZE(16)) value “1” means positive benefit and value “0” means negativebenefit. The remaining bits quantize the magnitude of benefit. All bitswith value “0” represent the special value that denotes CoMP HypothesisSet IE is mandated indication by the sending eNB. [>Time Granularity:FFS] [Starting SFN: FFS] [Starting Subframe Index: FFS] Range boundExplanation maxnoofCoMPInformation Maximum number of CoMP Hypothesissets. The value is FFS.

Example-2b

IE type and Semantics IE/Group Name Presence Range reference descriptionCoMP Information 1 . . . Item <maxnoofCoMPInformation> >CoMP HypothesisM 9.2.xy Set >Benefit Metric M BIT STRING The first left most bit: (SIZE(16)) value “0” means positive benefit and value “1” means negativebenefit. The remaining bits quantize the magnitude of benefit. All bitswith value “0” represent the special value that denotes CoMP HypothesisSet IE is mandated indication by the sending eNB. [>Time Granularity:FFS] [Starting SFN: FFS] [Starting Subframe Index: FFS] Range boundExplanation maxnoofCoMPInformation Maximum number of CoMP Hypothesissets. The value is FFS.

Example sizes for maxnoofCoMPInformation are 4, 8, 16, or 256.

Embodiment D

In the following we provide our views on X2 messages to support theinter-eNB CoMP along with the required message structure.

D1. CoMP Hypothesis for Inter-eNB CoMP

Each CoMP hypothesis (CH) contains a hypothetical resource allocationfor a cell that is not necessarily controlled by the receiving eNB. Thedesign of signaling associated with such CoMP hypotheses and associatedbenefit metrics must facilitate both centralized and distributed RRM.The use cases in both centralized and distributed RRM is described inthe appendix. Our preference for computing the benefit metric on alinear scale is justified there.

We next present our view on the coding structure of the CoMP hypothesis.

From the agreements made so far ([2] and [3]), it is clear that abenefit metric is associated with multiple CoMP hypotheses, where eachCoMP hypothesis indicates a resource allocation in the frequency domain(on a per-RB basis) as well as the time domain (across multiplesub-frames). The guiding principle behind benefit metric was that itcould be used to convey the change in a utility function in a succinctmanner. The utility function usually depends on several factors such asqueue sizes, channel states, priorities (or QoS classes) of the usersbeing served by that eNB or cell. The benefit metric has the potentialto convey the change resulting from a hypothetical resource allocation,without the need of signaling all the constituent terms of the utilityfunction. However, this potential can be realized only if the benefitmetric value represents a fine enough quantization. Moreover, apotentially serious drawback of not having a benefit metric field thatallows for a fine quantization of the utility change is that it can leadto oscillatory behavior in distributed coordination.

It is apparent that the amount of information we can convey using asingle benefit metric value (effective quantization level) becomesincreasingly diminished as we include more hypotheses in the CoMPhypothesis set, as well as when we increase the choices (possibilities)of the resource allocation that can be conveyed by each hypothesis.Thus, the predominant use case would be to have a limited CoMPhypothesis set size (which is controllable with the maximum being 32)and have limited choices of resource allocation possibilities conveyedby each hypothesis.

This can be achieved by conveying resource allocation associated witheach hypothesis across frequency (on a per-RB basis) and over one (or afew) sub-frames in the time domain (via a list). The pattern representedby the list is understood to be repeated continuously. Furthermore, itis sensible to restrict all patterns (corresponding to differenthypotheses in the set) to have the same size in terms of the number ofsub-frames spanned by them. Such a design permits all the flexibilityneeded by the typical use-cases and also achieves overhead reduction. Wefurther note that patterns of unequal sizes also complicate the benefitmetric computation. This design is described in our text proposal.

We discussed the necessary X2 message to support the inter-eNB CoMP andpresented corresponding text proposals.

D2. Text Proposal

9.2.xx CoMP Information

This IE provides the list of CoMP hypothesis sets, where each CoMPhypothesis set is the collection of CoMP hypothesis(ses) of one ormultiple cells and each CoMP hypothesis set is associated with a benefitmetric.

IE type and Semantics IE/Group Name Presence Range reference descriptionCoMP Information 1 . . . Item <maxnoofCoMPInformation> >CoMP HypothesisM 9.2.xy Set >CoMP Hypothesis M 1 . . . <maxnoofSubframes> The size ListSize (cardinality) of each CoMP Hypothesis list in the CoMP Hypothesisset. >Benefit Metric M INTEGER Value −100 indicates (−101 . . . themaximum cost, 100, . . . ) and 100 indicates the maximum benefit. Value−101 indicates unknown benefit. The value is computed on a linear scale.CoMP Information 0 . . . 1 Start Time >Start SFN M INTEGER SFN of theradio (0 . . . 1023) frame containing the first subframe when the CoMPInformation IE is valid. >Start Subframe M INTEGER Subframe number,Number (0 . . . 9) within the radio frame indicated by the Start SFN IE,of the first subframe when the CoMP Information IE is valid. Range boundExplanation maxnoofCoMPInformation Maximum number of CoMP Hypothesissets. The value is 256. maxnoofSubframes Maximum number of Subframes.The value is 40.

maxnoofSubframes can alternatively be 20 or 80.

9.2.xy CoMP Hypothesis Set

This IE provides a set of CoMP hypotheses. A CoMP hypothesis ishypothetical PRB-specific resource allocation information for a cell.

IE type and Semantics IE/Group Name Presence Range reference descriptionCoMP Hypothesis 1 . . . <maxnoof Set Element CoMPCells> >Cell ID M ECGIID of the cell for 9.2.14 which the CoMP Hypothesis IE is applied. >CoMPM CoMP The CoMP Hypothesis List Hypothesis Hypothesis List List Size IEis repeatedly applied. >>CoMP M BIT Each position in Hypothesis STRINGthe bitmap (6 . . . represents a 110, . . . ) PRB (i.e. first bit = PRB0 and so on), for which value “1” indicates interference protectedresource and value “0” indicates resource with no utilizationconstraints.

D3. Use of Special Value

In centralized RRM a typical use of CoMP hypothesis (CH) set would be amandatory resource allocation that each cell indicated in the respectiveCH will (or must) follow, whereas in a distributed RRM scenario the CHwould be a request which the indicated cell may or may not follow. As aresult, using a special value of the associated benefit metric toindicate whether the constituent resource allocations are mandatory ornot, is desirable. This is also useful when the CH is sent to the eNBnot controlling the indicated cell, since then the latter eNB can havemore information about the possible resource allocation of neighboringcells, to make its own resource allocation decision. An example ofcentralized coordination is given in FIG. 3(a), and that of adistributed coordination is given in FIG. 4. Note that in thedistributed case, eRNTP can be used to convey the resource allocationdecisions.

D4. Use of Benefit Metric

In the context of Section C1.2, we note that comparing different benefitmetric values for a given (hypothetical) resource allocation issimplified if these values are computed using a linear scale. In thatcase we can simply add the values together (after scaling or shifting)to assess the net benefit (or cost). The scaling or shifting parameters(if needed) can be determined by each eNB based on previously receivedreports. The other option is for an entity (operator) to provide eacheNB with a loop-up-table corresponding to each of its neighbors, whichthat eNB can use to first map each received benefit value to anestimated value using the appropriate look-up-table and then compare theestimated values. We slightly prefer the first option since the secondone is more complex.

APPENDIX OPTIMIZING PROPORTIONAL FAIRNESS UTILITY METRIC

Suppose that there are K users and B transmission nodes or transmissionpoints (TPs) in the CoMP cluster, i.e., coordination set or of interest,where these TPs can include multiple eNBs. For convenience inexposition, here we assume a full buffer traffic model and let Ω denotethe set of K users. We consider hybrid schemes where the assignment ofprecoding matrices (beamforming vectors or sectored beams) to the B TPsand the association of users with those TPs (i.e., point switching) aredone in a semi-static centralized manner based on average estimates ofSINRs, rates etc. On the other hand, given its assigned precoder (orbeam) and the users associated with it, each TP does per sub-framescheduling independently based on the instantaneous short-term CSI.

Let Ŵ=(W₁, . . . , W_(B)) denote an assignment of a precoder tuple,where W_(b) is the precoder assigned to the b^(th) TP. Here eachprecoder W_(b) can be chosen from a pre-determined finite set Ψ whichincludes a codeword 0 and W_(b)=0 means that the b^(th) TP is muted.Thus, SSPM is subsumed as a special case.

Then, let R_(u) ^(b)(Ŵ) denote an estimate of the average rate that useru can obtain (over the available time-frequency resource normalized tohave size unity) when it is served data by TP b, given that the precodertuple Ŵ is assigned to the B TPs and that no other user is associatedwith TP b. This time-frequency unit could for example be a set ofresource blocks. Next, suppose that m total users are associated with TPb. Following the conventional approach, the average rate that user u canthen obtain under proportional fair per-subframe scheduling can beapproximated as

$\frac{R_{u}^{b}\left( \hat{W} \right)}{m}.$

With these definitions in hand, we can jointly determine the assignmentof a precoding tuple and the user association (i.e., jointly considersemi-static coordinated beamforming (SSCB) and semi-static coordinatedpoint-switching (SSPS) problems) by solving the following optimizationproblem:

$\begin{matrix}{{\max_{\hat{W},{\{ x_{u,b}\}}}\left\{ {\sum\limits_{u,b}^{\;}{x_{u,b}{\log\left( \frac{R_{u}^{b}\left( \hat{W} \right)}{\sum\limits_{k}^{\;}x_{k,b}} \right)}}} \right\}}{{{s.t.\mspace{14mu} {\sum\limits_{b}^{\;}x_{u,b}}} = 1},{{\forall u};{x_{u,b} \in \left\{ {0,1} \right\}}},{\forall u},b}{{\hat{W} = \left( {W_{1},\ldots \mspace{14mu},W_{B}} \right)},{W_{i} \in \Psi},{\forall i}}} & ({P1})\end{matrix}$

Note that in (P1), each x_(u,b) is an indicator variable which is equalto one if user u is associated with TP b and zero otherwise. Thereforethe constraint in (P1) enforces that each user must be associated withonly one TP. It can be shown that (P1) cannot be solved optimally in anefficient manner, which necessitates the design of low-complexityalgorithms that can approximately solve (P1). For any given precodertuple Ŵ the SSPS sub-problem can be optimally solved. Alternatively, agreedy approach can be adopted to achieve further complexity reduction.

These solutions to the SSPS problem can be leveraged to obtain analgorithm to sub-optimally solve the joint SSCB and SSPS problem (P1).

We next consider the SSPM-only problem where user associations arepre-determined.

$\begin{matrix}{{\max_{\hat{W}}\left\{ {\sum\limits_{b,{u \in S_{b}}}^{\;}{\log\left( \frac{R_{u}^{b}\left( \hat{W} \right)}{S_{b}} \right)}} \right\}}{{{s.t.\mspace{14mu} \hat{W}} = \left( {W_{1},\ldots \mspace{14mu},W_{B}} \right)},{W_{i} \in \Psi},{\forall i}}} & ({P2})\end{matrix}$

Here S_(b) denotes the pre-determined set of users associated to TP band |S_(b)| denotes its cardinality.

(P2) is also in general a hard problem which cannot be solved optimallyin an efficient manner. Good heuristics can nevertheless be developed tosolve (P2).

The foregoing is to be understood as being in every respect illustrativeand exemplary, but not restrictive, and the scope of the inventiondisclosed herein is not to be determined from the Detailed Description,but rather from the claims as interpreted according to the full breadthpermitted by the patent laws. It is to be understood that theembodiments shown and described herein are only illustrative of theprinciples of the present invention and that those skilled in the artmay implement various modifications without departing from the scope andspirit of the invention. Those skilled in the art could implementvarious other feature combinations without departing from the scope andspirit of the invention.

1-14. (canceled)
 15. A wireless communication method implemented in a first base station, the wireless communication method comprising: communicating with a user equipment; and transmitting, to a second base station, a Coordinated Multi-Point transmission (CoMP) information, which the CoMP information comprises a table described below: IE/Group Name Presence Range CoMP Information Item 1 . . . <maxnoofCoMPInformation> >CoMP Hypothesis Set M >Benefit Metric M Start SFN Start Subframe Index

where M denotes mandatory, and maxnoofCoMPinformation denotes a Maximum number of CoMP Hypothesis sets.
 16. The wireless communications method according to claim 15, wherein the benefit metric is between a negative value and a positive value, inclusive.
 17. The wireless communications method according to claim 15, wherein the CoMP Hypothesis Set includes at least an ID related to a cell.
 18. The wireless communications method according to claim 15, wherein the CoMP Hypothesis Set includes at least a CoMP Hypothesis.
 19. The wireless communications method according to claim 15, wherein the maxnoofCoMPinformation is 4, 8, 16, or
 256. 20. The wireless communications method according to claim 15, wherein the CoMP information is transmitted via X2 interface.
 21. The wireless communications method according to claim 15, wherein the benefit metric is calculated on a liner scale.
 22. The wireless communications method according to claim 15, wherein the benefit metric comprises null or special value indicating information other than benefit.
 23. The wireless communications method according to claim 22, wherein the information is an unknown benefit.
 24. The wireless communications method according to claim 15, wherein the benefit metric indicates a loss or cost when the benefit metric is a negative value.
 25. A first base station comprising: a controller configured to communicate with a user equipment; and a transmission interface configured to transmit, to a second base station, a Coordinated Multi-Point transmission (CoMP) information, which the CoMP information comprises a table described below: IE/Group Name Presence Range CoMP Information Item 1 . . . <maxnoofCoMPInformation> >CoMP Hypothesis Set M >Benefit Metric M Start SFN Start Subframe Index

where M denotes mandatory, and maxnoofCoMPinformation denotes a Maximum number of CoMP Hypothesis sets.
 26. The first base station according to claim 25, wherein the benefit metric is between a negative value and a positive value, inclusive.
 27. The first base station according to claim 25, wherein the CoMP Hypothesis Set includes at least an ID related to a cell.
 28. The first base station according to claim 25, wherein the CoMP Hypothesis Set includes at least a CoMP Hypothesis.
 29. The first base station according to claim 25, wherein the maxnoofCoMPinformation is 4, 8, 16, or
 256. 30. The first base station according to claim 25, wherein the CoMP information is transmitted via X2 interface.
 31. The first base station according to claim 25, wherein the benefit metric is calculated on a liner scale.
 32. The first base station according to claim 25, wherein the benefit metric comprises null or special value indicating information other than benefit.
 33. The first base station according to claim 32, wherein the information is an unknown benefit.
 34. The wireless communications method according to claim 25, wherein the benefit metric indicates a loss or cost when the benefit metric is the negative value.
 35. A wireless communication system comprising: a first base station; and a second base station configured to transmit, to the first base station, a Coordinated Multi-Point transmission (CoMP) information, which the CoMP information comprises a table described below: IE/Group Name Presence Range CoMP Information 1 . . . <maxnoofCoMPInformation> Item >CoMP Hypothesis M Set >Benefit Metric M Start SFN Start Subframe Index

where M denotes mandatory, and maxnoofCoMPinformation denotes a Maximum number of CoMP Hypothesis sets.
 36. The wireless communication system according to claim 35, wherein the benefit metric is between a negative value and a positive value, inclusive. 